{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.数据准备"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.1 读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60000, 28, 28) (60000,)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "data_filePath = '../resources/MNIST_data/mnist.npz'\n",
    "data = np.load(data_filePath)\n",
    "train_x, train_y = data['x_train'], data['y_train']\n",
    "print(train_x.shape, train_y.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2 查看数据可视化的图片"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 64 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import math\n",
    "import numpy as np\n",
    "\n",
    "def draw_digit(position, image, title):\n",
    "    plt.subplot(*position)\n",
    "    plt.imshow(image.reshape(-1, 28), cmap='gray_r')\n",
    "    plt.axis('off')\n",
    "    plt.title(title)\n",
    "    \n",
    "def batch_draw(batch_size):\n",
    "    selected_indexes = np.random.choice(np.arange(60000), batch_size)\n",
    "    images, labels = train_x[selected_indexes], train_y[selected_indexes]\n",
    "    image_number = images.shape[0]\n",
    "    row_number = math.ceil(image_number ** 0.5)\n",
    "    column_number = row_number\n",
    "    plt.figure(figsize=(row_number, column_number))\n",
    "    for i in range(row_number):\n",
    "        for j in range(column_number):\n",
    "            index = i * column_number + j\n",
    "            if index < image_number:\n",
    "                position = (row_number, column_number, index+1)\n",
    "                image = images[index]\n",
    "                label = labels[index]\n",
    "                title = 'actual:%d' %label\n",
    "                draw_digit(position, image, title)\n",
    "\n",
    "batch_draw(64)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.搭建神经网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "class Net_1(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net_1, self).__init__()\n",
    "        self.linear_1 = nn.Linear(784, 10)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = torch.from_numpy(x.reshape(-1, 784)).float()\n",
    "        y = self.linear_1(x)\n",
    "        return y\n",
    "    \n",
    "    \n",
    "class Net_2(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net_2, self).__init__()\n",
    "        self.linear_1 = nn.Linear(784, 300)\n",
    "        self.linear_2 = nn.Linear(300, 10)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = torch.from_numpy(x.reshape(-1, 784)).float()\n",
    "        x = self.linear_1(x).clamp(min=0)\n",
    "        y = self.linear_2(x)\n",
    "        return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.定义损失函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_function = nn.CrossEntropyLoss()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.在训练集上训练网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "# 实时更新进度条\n",
    "def print_flush(print_string):\n",
    "    print(print_string, end='\\r')\n",
    "    sys.stdout.flush()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step:2000 loss_value:0.081328 accuracy_value:0.9700\r"
     ]
    }
   ],
   "source": [
    "net = Net_2()\n",
    "optimizer = torch.optim.Adam(net.parameters(), lr=1e-4)\n",
    "steps = 2000\n",
    "batch_size = 100\n",
    "index_1dArray = np.arange(60000)\n",
    "for i in range(steps+1):\n",
    "    batch_indexes = np.random.choice(index_1dArray, batch_size)\n",
    "    # 前向传播\n",
    "    batch_x = train_x[batch_indexes]\n",
    "    predicted_Y = net(batch_x)\n",
    "    # 计算损失值\n",
    "    batch_y = train_y[batch_indexes]\n",
    "    input_y = torch.from_numpy(batch_y).long()\n",
    "    loss = loss_function(predicted_Y, input_y)\n",
    "    loss_value = loss.item()\n",
    "    # 计算准确率\n",
    "    predicted_y = predicted_Y.argmax(axis=1)\n",
    "    accuracy = (predicted_y==input_y).float().mean()\n",
    "    accuracy_value = accuracy.item()\n",
    "    # 每隔20步，打印训练记录\n",
    "    if i % 20 == 0:\n",
    "        print_flush('step:%d loss_value:%.6f accuracy_value:%.4f' %(\n",
    "            i, loss_value, accuracy_value))\n",
    "    # 反向传播\n",
    "    optimizer.zero_grad()\n",
    "    loss.backward()\n",
    "    optimizer.step()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.模型测试"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.1 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9489\n"
     ]
    }
   ],
   "source": [
    "test_x, test_y = data['x_test'], data['y_test']\n",
    "predicted_Y = net(test_x)\n",
    "predicted_y = predicted_Y.argmax(axis=1).numpy()\n",
    "accuracy = (test_y==predicted_y).astype('float').mean()\n",
    "print(accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.2 模型实用效果可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1296 with 100 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_digit_2(position, image, title, isTrue):\n",
    "    plt.subplot(*position)\n",
    "    plt.imshow(image.reshape(-1, 28), cmap='gray_r')\n",
    "    plt.axis('off')\n",
    "    if not isTrue:\n",
    "        plt.title(title, color='red')\n",
    "    else:\n",
    "        plt.title(title)\n",
    "        \n",
    "def batch_draw_2(batch_size):\n",
    "    # 选出批量数据\n",
    "    index_1dArray = np.arange(len(test_x))\n",
    "    batch_indexes = np.random.choice(index_1dArray, batch_size)\n",
    "    batch_x = test_x[batch_indexes]\n",
    "    batch_y = test_y[batch_indexes]\n",
    "    # 使用模型预测出结果\n",
    "    predicted_y = net(batch_x).argmax(axis=1).numpy()\n",
    "    # 规划画图行列数量\n",
    "    image_number = batch_x.shape[0]\n",
    "    row_number = math.ceil(image_number ** 0.5)\n",
    "    column_number = row_number\n",
    "    plt.figure(figsize=(row_number+8, column_number+8))\n",
    "    # 循环遍历绘画每张子图\n",
    "    for i in range(row_number):\n",
    "        for j in range(column_number):\n",
    "            index = i * column_number + j\n",
    "            if index < image_number:\n",
    "                position = (row_number, column_number, index+1)\n",
    "                image = batch_x[index]\n",
    "                actual = batch_y[index]\n",
    "                predict = predicted_y[index]\n",
    "                isTrue = actual==predict\n",
    "                title = 'actual:%d\\npredict:%d' %(actual,predict)\n",
    "                draw_digit_2(position, image, title, isTrue)\n",
    "                \n",
    "batch_draw_2(100)                "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6.卷积神经网络"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1 搭建神经网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Net_3(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net_3, self).__init__()\n",
    "        self.relu = nn.ReLU()\n",
    "        self.bn_1 = nn.BatchNorm2d(1)\n",
    "        self.conv_1 = nn.Conv2d(1, 32, (5,5), padding=1) # N * 28 * 28 * 32\n",
    "        self.maxpool_1 = nn.MaxPool2d(2, 2, padding=1) # N * 14 * 14 * 32\n",
    "        self.bn_2 = nn.BatchNorm2d(32)\n",
    "        self.conv_2 = nn.Conv2d(32, 64, (5,5), padding=1) # N * 14 * 14 * 64\n",
    "        self.maxpool_2 = nn.MaxPool2d(2, 2, padding=1) # N * 7 * 7 * 64\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.bn_3 = nn.BatchNorm1d(7 * 7 * 64)\n",
    "        self.linear_1 = nn.Linear(7 * 7 * 64, 128)\n",
    "        self.bn_4 = nn.BatchNorm1d(128)\n",
    "        self.linear_2 = nn.Linear(128, 10)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = x.permute(0, 3, 1, 2)\n",
    "        # 第1层卷积\n",
    "        x = self.bn_1(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.conv_1(x)\n",
    "        x = self.maxpool_1(x)\n",
    "        # 第2层卷积\n",
    "        x = self.bn_2(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.conv_2(x)\n",
    "        x = self.maxpool_2(x)\n",
    "        # 2维矩阵展平为1维矩阵\n",
    "        x = self.flatten(x)\n",
    "        # 第1层全连接\n",
    "        x = self.bn_3(x)\n",
    "        x = self.relu(x)\n",
    "        x = self.linear_1(x)\n",
    "        # 第2层全连接\n",
    "        x = self.bn_4(x)\n",
    "        x = self.relu(x)\n",
    "        y = self.linear_2(x)\n",
    "        return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2 在训练集上训练网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "step:2000 loss_value:0.011762 accuracy_value:0.9900\r"
     ]
    }
   ],
   "source": [
    "net = Net_3()\n",
    "device = torch.device('cuda')\n",
    "net.to(device)\n",
    "optimizer = torch.optim.Adam(net.parameters(), lr=1e-3)\n",
    "steps = 2000\n",
    "batch_size = 200\n",
    "index_1dArray = np.arange(60000)\n",
    "tensor_x = torch.from_numpy(train_x.reshape(-1, 28, 28, 1)).float()\n",
    "tensor_y = torch.from_numpy(train_y).long()\n",
    "for i in range(steps+1):\n",
    "    batch_indexes = np.random.choice(index_1dArray, batch_size)\n",
    "    # 前向传播\n",
    "    batch_x = tensor_x[batch_indexes]\n",
    "    input_x = batch_x.to(device)\n",
    "    predicted_Y = net(input_x)\n",
    "    # 计算损失值\n",
    "    batch_y = tensor_y[batch_indexes]\n",
    "    input_y = batch_y.to(device)\n",
    "    loss = loss_function(predicted_Y, input_y)\n",
    "    loss_value = loss.item()\n",
    "    # 计算准确率\n",
    "    predicted_y = predicted_Y.argmax(axis=1)\n",
    "    accuracy = (predicted_y==input_y).float().mean()\n",
    "    accuracy_value = accuracy.item()\n",
    "    # 每隔20步，打印训练记录\n",
    "    if i % 20 == 0:\n",
    "        print_flush('step:%d loss_value:%.6f accuracy_value:%.4f' %(\n",
    "            i, loss_value, accuracy_value))\n",
    "    # 反向传播\n",
    "    optimizer.zero_grad()\n",
    "    loss.backward()\n",
    "    optimizer.step()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.3 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9914\n"
     ]
    }
   ],
   "source": [
    "test_x, test_y = data['x_test'], data['y_test']\n",
    "predicted_y = np.zeros((len(test_y),))\n",
    "for i in range(0, len(test_x), batch_size):\n",
    "    start_index = i\n",
    "    end_index = i + batch_size\n",
    "    x = test_x[start_index: end_index]\n",
    "    input_x = torch.from_numpy(x.reshape(-1, 28, 28, 1)).float()\n",
    "    input_x = input_x.to(device)\n",
    "    predicted_Y = net(input_x)\n",
    "    predicted_y[start_index:end_index] = predicted_Y.argmax(axis=1).cpu().numpy()\n",
    "accuracy = (test_y==predicted_y).astype('float').mean()\n",
    "print(accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
